evaluation

SKILL.md

Evaluation of agent systems requires different approaches than traditional software or even standard language model applications. Agents make dynamic decisions, are non-deterministic between runs, and often lack single correct answers. Effective evaluation must account for these characteristics while providing actionable feedback. A robust evaluation framework enables continuous improvement, catches regressions, a...

Agent evaluation requires outcome-focused approaches that account for non-determinism and multiple valid paths. Multi-dimensional rubrics capture various quality aspects: factual accuracy, completeness, citation accuracy, source quality, and tool efficiency. LLM-as-judge provides scalable evaluation while human evaluation catches edge cases.

The key insight is that agents may find alternative paths to goals—the evaluation should judge whether they achieve right outcomes while following reasonable processes.

當用戶要求“評估代理性能”、“構建測試框架”、“衡量代理質量”、“創建評估標準”，或提到 LLM 作為法官、多維評估、代理測試或代理管道的質量門時，應使用此技能。 來源：muratcankoylan/agent-skills-for-context-engineering。

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